[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-5-llm-benchmarks-for-business-buyers-2026-zh":3,"article-related-5-llm-benchmarks-for-business-buyers-2026-zh":33,"series-industry-a7bca854-a4d9-4616-b651-e5d732a63255":86},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":16,"key_takeaways":25,"views":29,"created_at":30,"published_at":31,"topic_cluster_id":32},"a7bca854-a4d9-4616-b651-e5d732a63255","5-llm-benchmarks-for-business-buyers-2026-zh","5 個 LLM 基準測試","\u003Cp data-speakable=\"summary\">這篇整理 5 個 LLM 基準測試，幫你判斷模型強弱、看懂分數失真，並選出最適合商務採購的測試。\u003C\u002Fp>\u003Cp>LLM 的分數看起來很明確，但到了 2026 年，只有部分測試還能反映真實表現。前沿模型在 GPQA Diamond 已到 94.3%，在 GSM8K 也逼近 99%，所以更重要的是：哪一個測試真的對應你的業務場景。\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>項目\u003C\u002Fth>\u003Cth>測什麼\u003C\u002Fth>\u003Cth>目前訊號\u003C\u002Fth>\u003Cth>最適合\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>MMLU\u003C\u002Ftd>\u003Ctd>57 個學科的廣泛知識\u003C\u002Ftd>\u003Ctd>頂尖分數 93%\u003C\u002Ftd>\u003Ctd>通用篩選、中階模型比較\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>GPQA Diamond\u003C\u002Ftd>\u003Ctd>博士級科學推理\u003C\u002Ftd>\u003Ctd>頂尖分數 94.3%\u003C\u002Ftd>\u003Ctd>高難推理、前沿模型比較\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>HumanEval\u003C\u002Ftd>\u003Ctd>Python 程式生成\u003C\u002Ftd>\u003Ctd>頂尖分數 93%\u003C\u002Ftd>\u003Ctd>快速 coding 檢查\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>SWE-bench Verified\u003C\u002Ftd>\u003Ctd>真實 GitHub 問題修復\u003C\u002Ftd>\u003Ctd>頂尖分數 80.8%\u003C\u002Ftd>\u003Ctd>軟體工程評估\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>LiveCodeBench\u003C\u002Ftd>\u003Ctd>抗污染 coding 測試\u003C\u002Ftd>\u003Ctd>頂尖分數 83.6%\u003C\u002Ftd>\u003Ctd>持續追蹤 coding 能力\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>1. MMLU\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F\">MMLU\u003C\u002Fa> 是這 5 個裡最廣的通用知識測試，涵蓋 57 個學科、超過 16,000 題\u003Ca href=\"\u002Fnews\u002Fwhy-halo-on-ps5-is-the-right-move-for-microsoft-zh\">選擇\u003C\u002Fa>題。當你想快速看一個模型能不能處理跨領域提示，這個分數仍然很有用。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779161051251-hgbf.png\" alt=\"5 個 LLM 基準測試\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>它的問題是開始飽和。前沿模型已推到 93%，所以它更適合區分弱模型與中階模型，不太適合拿來分辨最頂尖的幾個系統。\u003C\u002Fp>\u003Cul>\u003Cli>測量面向：知識與推理\u003C\u002Fli>\u003Cli>題型：選擇題\u003C\u002Fli>\u003Cli>適合用途：初步篩選\u003C\u002Fli>\u003Cli>不適合：最後的前沿排名\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>2. GPQA Diamond\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F\">GPQA Diamond\u003C\u002Fa> 適合你想測更硬的推理能力。它用生物、化學、物理等專家級題目，仍保留足夠難度來區分頂尖模型。\u003C\u002Fp>\u003Cp>截至 2026 年 2 月，\u003Ca href=\"\u002Ftag\u002Fgemini\">Gemini\u003C\u002Fa> 3.1 Pro 以 94.3% 領先，\u003Ca href=\"\u002Ftag\u002Fclaude\">Claude\u003C\u002Fa> Opus 4.6 為 91.3%，GPT-5.3 \u003Ca href=\"\u002Ftag\u002Fcodex\">Codex\u003C\u002Fa> 為 81%，Qwen3.5-plus 也接近 88.4%。這種差距表示它在頂端仍有辨識力。\u003C\u002Fp>\u003Cul>\u003Cli>測量面向：高階科學推理\u003C\u002Fli>\u003Cli>題型：博士級選擇題\u003C\u002Fli>\u003Cli>適合用途：前沿模型比較\u003C\u002Fli>\u003Cli>要注意：頂端仍可能逐步飽和\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>3. HumanEval\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F\">HumanEval\u003C\u002Fa> 仍是最容易理解的 coding 測試，因為它很直觀：164 個 Python 任務，全部靠單元測試驗證。如果你要做 demo、內部初選或快速檢查，這仍是好起點。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779161052017-q0f0.png\" alt=\"5 個 LLM 基準測試\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>但它已不算強力的前沿區分器。GPT-5.3 Codex 已到 93%，再加上污染問題存在，商務決策上應把它當第一關，而不是最後答案。\u003C\u002Fp>\u003Cul>\u003Cli>測量面向：程式生成\u003C\u002Fli>\u003Cli>語言：Python\u003C\u002Fli>\u003Cli>驗證方式：功能單元測試\u003C\u002Fli>\u003Cli>適合用途：快速基線檢查\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>4. SWE-bench Verified\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F\">SWE-bench Verified\u003C\u002Fa> 更接近真實軟體工作。它不是孤立題目，而是要求模型修補真實 \u003Ca href=\"\u002Ftag\u002Fgithub\">GitHub\u003C\u002Fa> issue，模型必須理解上下文、找出 bug，還要產出能通過測試的 patch。\u003C\u002Fp>\u003Cp>如果你關心開發者效率或 coding agent，這是最值得追的指標之一。Claude Opus 4.6 以 80.8% 領先，MiniMax-M2.5 為 80.2%，Gemini 3.1 Pro 為 80.6%，顯示頂尖系統之間競爭很接近。\u003C\u002Fp>\u003Cul>\u003Cli>測量面向：端到端軟體工程\u003C\u002Fli>\u003Cli>任務類型：真實 repository issue\u003C\u002Fli>\u003Cli>適合用途：agentic coding 評估\u003C\u002Fli>\u003Cli>優勢：比合成題更難作弊\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>5. LiveCodeBench\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F\">LiveCodeBench\u003C\u002Fa> 適合想要「分數還跟得上現況」的團隊。\u003Ca href=\"\u002Fnews\u002Fwhy-halo-on-ps5-is-the-right-move-zh\">它會\u003C\u002Fa>定期更新題庫，降低訓練資料污染，也讓測試能隨著模型進步持續保持價值。\u003C\u002Fp>\u003Cp>這對追蹤版本更新很重要。Qwen3.5-plus 在第 6 版以 83.6% 領先，而這個數字之所以更有意義，就是因為題庫會變動，較不容易被背題\u003Ca href=\"\u002Fnews\u002F5-claudes-credit-caps-impact-zh\">影響\u003C\u002Fa>。\u003C\u002Fp>\u003Ccode>LiveCodeBench 適合：1) 需要抗記憶化的 coding 測試，2) 想按月追蹤分數，3) 想看更貼近當前模型行為的比較。\u003C\u002Fcode>\u003Ch2>怎麼挑\u003C\u002Fh2>\u003Cp>如果你要先做廣泛篩選，從 MMLU 開始。若工作重點是高難推理，GPQA Diamond 更有訊號。對軟體團隊來說，HumanEval 可當快速檢查，但真要看實際 coding 能力，\u003Ca href=\"\u002Ftag\u002Fswe-bench-verified\">SWE-bench Verified\u003C\u002Fa> 和 LiveCodeBench 更可靠。\u003C\u002Fp>\u003Cp>最重要的原則很簡單：讓基準測試對應你的工作。只有當題目接近生產任務、資料夠乾淨，而且測試本身還有足夠區分度時，高分才真的有意義。\u003C\u002Fp>","5 個基準測試幫你判斷模型強弱、看懂分數失真，並選出最適合商務採購的測試。","www.lxt.ai","https:\u002F\u002Fwww.lxt.ai\u002Fblog\u002Fllm-benchmarks\u002F",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779161051251-hgbf.png","industry","zh","9b2db204-7090-4a48-85e0-65693e66152e",[17,18,19,20,21,22,23,24],"LLM benchmarks","MMLU","GPQA Diamond","HumanEval","SWE-bench Verified","LiveCodeBench","business buyers","2026",[26,27,28],"MMLU 適合通用篩選，不適合判定最頂尖模型。","GPQA Diamond 仍能有效區分高階推理能力。","SWE-bench Verified 和 LiveCodeBench 更接近真實 coding 工作。",7,"2026-05-19T03:23:38.737225+00:00","2026-05-19T03:23:38.64+00:00","7aa69b8b-ff49-4d68-9e8b-f08e577b1239",{"tags":34,"relatedLang":45,"relatedPosts":49},[35,37,39,41,43],{"name":18,"slug":36},"mmlu",{"name":19,"slug":38},"gpqa-diamond",{"name":21,"slug":40},"swe-bench-verified",{"name":20,"slug":42},"humaneval",{"name":17,"slug":44},"llm-benchmarks",{"id":15,"slug":46,"title":47,"language":48},"5-llm-benchmarks-for-business-buyers-2026-en","5 LLM benchmarks for business buyers in 2026","en",[50,56,62,68,74,80],{"id":51,"slug":52,"title":53,"cover_image":54,"image_url":54,"created_at":55,"category":13},"06734645-2e2f-4903-9e47-e6ac889e34b7","game-thread-prompt-turns-nba-chatter-into-template-zh","Game-thread prompt 把聊天變模板","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780547608583-tp2j.png","2026-06-04T04:33:05.772212+00:00",{"id":57,"slug":58,"title":59,"cover_image":60,"image_url":60,"created_at":61,"category":13},"c323ffb6-20c8-468a-9d37-68e801588ee5","5-takeaways-from-spurs-vs-trail-blazers-game-5-zh","5 個 Spurs 對 Trail Blazers Game 5 重點","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780546677776-oc0j.png","2026-06-04T04:17:25.558061+00:00",{"id":63,"slug":64,"title":65,"cover_image":66,"image_url":66,"created_at":67,"category":13},"0231f359-f786-4e6c-8104-d3fae443f98b","4-chipotle-promo-details-for-members-zh","4 個 Chipotle 會員活動重點","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780540375071-5xa3.png","2026-06-04T02:32:19.54736+00:00",{"id":69,"slug":70,"title":71,"cover_image":72,"image_url":72,"created_at":73,"category":13},"39e4c1b2-4a8d-4baf-86eb-f65d4f6c3624","why-chipotle-53000-burrito-stunt-smart-brand-marketing-zh","為什麼 Chipotle 的 53,000 捲餅活動是聰明的品牌行銷","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780538579630-nkln.png","2026-06-04T02:02:28.454411+00:00",{"id":75,"slug":76,"title":77,"cover_image":78,"image_url":78,"created_at":79,"category":13},"53955aa8-9120-41c1-b342-6ca40e24b6ee","apples-gemini-deal-turns-cloud-ai-into-local-ai-zh","Apple 把雲端 AI 拆成本機 AI","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780535908899-g9ua.png","2026-06-04T01:18:03.319604+00:00",{"id":81,"slug":82,"title":83,"cover_image":84,"image_url":84,"created_at":85,"category":13},"a1119341-06e2-47ed-95f0-192f89c277a7","sec-draft-plan-puts-crypto-rules-first-zh","SEC草案把加密規則排第一","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780534108464-yi2d.png","2026-06-04T00:48:00.749142+00:00",[87,92,97,102,107,112,117,122,127,132],{"id":88,"slug":89,"title":90,"created_at":91},"ee073da7-28b3-4752-a319-5a501459fb87","ai-in-2026-what-actually-matters-now-zh","2026 AI 真正重要的事","2026-03-26T07:09:12.008134+00:00",{"id":93,"slug":94,"title":95,"created_at":96},"83bd1795-8548-44c9-9a7e-de50a0923f71","trump-ai-framework-power-speech-state-preemption-zh","川普 AI 框架瞄準電力、言論與州權","2026-03-26T07:12:18.695466+00:00",{"id":98,"slug":99,"title":100,"created_at":101},"ea6be18b-c903-4e54-97b7-5f7447a612e0","nvidia-gtc-2026-big-ai-announcements-zh","NVIDIA GTC 2026 重點拆解","2026-03-26T07:14:26.62638+00:00",{"id":103,"slug":104,"title":105,"created_at":106},"4bcec76f-4c36-4daa-909f-54cd702f7c93","claude-users-spreading-out-and-getting-better-zh","Claude 用戶更分散，也更會用","2026-03-26T07:22:52.325888+00:00",{"id":108,"slug":109,"title":110,"created_at":111},"bd903b15-2473-4178-9789-b7557816e535","openclaw-raises-hard-question-for-ai-models-zh","OpenClaw 逼問 AI 模型價值","2026-03-26T07:24:54.707486+00:00",{"id":113,"slug":114,"title":115,"created_at":116},"eeac6b9e-ad9d-4831-8eec-8bba3f9bca6a","gap-google-gemini-checkout-fashion-search-zh","Gap 把結帳搬進 Gemini","2026-03-26T07:28:23.937768+00:00",{"id":118,"slug":119,"title":120,"created_at":121},"0740e53f-605d-4d57-8601-c10beb126f3c","google-pushes-gemini-transition-to-march-2026-zh","Google 把 Gemini 轉換延到 2026 年 3…","2026-03-26T07:30:12.825269+00:00",{"id":123,"slug":124,"title":125,"created_at":126},"e660d801-2421-4529-8fa9-86b82b066990","metas-llama-4-benchmark-scandal-gets-worse-zh","Meta Llama 4 分數風波又擴大","2026-03-26T07:34:21.156421+00:00",{"id":128,"slug":129,"title":130,"created_at":131},"183f9e7c-e143-40bb-a6d5-67ba84a3a8bc","accenture-mistral-ai-sovereign-enterprise-deal-zh","Accenture 攜手 Mistral AI 賣主權 AI","2026-03-26T07:38:14.818906+00:00",{"id":133,"slug":134,"title":135,"created_at":136},"191d9b1b-768a-478c-978c-dd7431a38149","mistral-ai-faces-its-hardest-year-yet-zh","Mistral AI 迎來最硬的一年","2026-03-26T07:40:23.716374+00:00"]